CLUTTER REJECTION SIGNAL PROCESSING

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$162,867.00
Award Year:
1993
Program:
SBIR
Phase:
Phase II
Contract:
n/a
Award Id:
15023
Agency Tracking Number:
15023
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
500 West Cummings Park Ste 395, Woburn, MA, 01801
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Raman Mehra Shah Mahmood
Principal Investigator
(617) 933-5355
Business Contact:
() -
Research Institution:
n/a
Abstract
INFARED SENSORS USED FOR SURVEILLANCE MUST BE ABLE TO DISCRIMINATE UNRESOLVED TARGETS AGAINST A CLUTTERED BACKGROUND WHICH MAY CONTAIN CLOUDS, SEA OR TERRAIN. ONE OF THE IMPORTANT PROBLEMS ASSOCIATED WITH THIS TASK IS TEMPORAL PROCESSING IN WHICH THE TARGET MOVEMENT RELATIVE TO BOTH BACKGROUND AND FOREGROUND CLUTTER IS USED TO ENHANCE DETECTION PROBABILITY. IN THIS PROPOSAL, WE PRESENT AN INTEGRATED AND POWERFUL APPROACH TO THIS PROBLEM WHICH HAS THE POTENTIAL TO YIELD SUPERIOR PERFORMANCE TO CURRENT TECHNOLOGY SUCH AS MTI. CURRENT ALGORITHMS TEND TO BE AD HOC, CONSISTING OF A CASCADE OF PROCESSORS WHICH MAY WORK AT CROSS PURPOSES. A MORE SUITABLE APPROACH WOULD BE TO COMBINE MOTION DETECTION AND CLUTTER REDUCTION IN A SINGLE STEP. WE PROPOSE A PROBABILISTIC FRAMEWORK IN WHICH THE IMAGE IS MODELED AS A RANDOM FIELD TO BE ESTIMATED IN REAL TIME FROM NOISY AMBIGUOUS MEASUREMENTS FROM MULTIPLE SENSORS. A BAYESIAN VIEWPOINT S ADOPTED, IN WHICH THE PRIOR KNOWLEDGE IS EXPRESSED AS A PROBABILITY DISTRIBUTI ON. USING A PROBABLISTICS DESCRIPTION OF THE OBSERVATION NOISE, THE POSTERIOR DISTRIBUTION OF THE RANDOM FIELD CAN BE COMPUTED. THESE MODELS ARE BASED ON MARKOV RANDOM FIELDS AND THE GIBBS DISTRIBUTION. SIGNIFICANTLY, THESE ASSUMPTIONS LEAD TO COOPERATIVE DISTRIBUTION ALGORITHMS WHICH MAY BE IMPLEMENTED ON PARALLEL PROCESSORS. IT IS POSSIBLE TO MODEL BOTH PIECEWISE CONTINUOUS SURFACES AND THE BOUNDARIES BETWEEN SMOOTH PATCHES (TARGETS, CLOUDS, OBJECTS, E.G.). THE PARAMETERS THAT APPEAR IN THE RECONSTRU CTION ALGORITHMS HAVE A PRECISE STATISTICAL INTERPRETATION WHICH MAY BE VALIDATED ON PHYSICAL GROUNDS.

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government